无人艇编队避碰路径规划与重规划

doi:10.12305/j.issn.1001-506X.2025.06.24

系统工程与电子技术 ›› 2025, Vol. 47 ›› Issue (6): 1964-1974.doi: 10.12305/j.issn.1001-506X.2025.06.24

无人艇编队避碰路径规划与重规划

刘伊婕¹^,², 姜斌¹^,²^,*, 马亚杰¹^,², 李文博¹^,³, 刘成瑞¹^,³

1. 南京航空航天大学自动化学院, 江苏南京 211106
2. 飞行器自主控制技术教育部工程研究中心, 江苏南京 211106
3. 北京控制工程研究所空间智能控制技术全国重点实验室, 北京 100094

收稿日期:2024-06-05 出版日期:2025-06-25 发布日期:2025-07-09
通讯作者: 姜斌
作者简介:刘伊婕 (2000—), 女, 硕士研究生, 主要研究方向为无人艇避碰路径规划与容错控制
姜斌 (1966—), 男, 教授, 博士, 主要研究方向为故障诊断与容错控制及应用
马亚杰 (1987—), 男, 教授, 博士, 主要研究方向为自适应故障诊断与容错控制
李文博 (1984—), 男, 高级工程师, 博士, 主要研究方向为故障诊断与容错控制、系统可诊断性评价与设计
刘成瑞 (1978—), 男, 研究员, 博士, 主要研究方向为控制系统故障诊断与容错控制
基金资助:
国家自然科学基金(62273177);国家自然科学基金(62020106003);国家自然科学基金(62233009);江苏省自然科学基金(BK20211566);江苏省自然科学基金(BK20222012);高校学科创新引智基地(B20007);空间智能控制技术全国重点实验室开放基金(HTKJ2023KL502006);中央高校基本科研业务费(NI2024001)

Collision avoidance path planning and re-planning for USV formation

Yijie LIU¹^,², Bin JIANG¹^,²^,*, Yajie MA¹^,², Wenbo LI¹^,³, Chengrui LIU¹^,³

1. College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China
2. Engineering Research Center of Autonomous Control Technology of Aircraft, Ministry of Education, Nanjing 211106, China
3. National Key Laboratory of Space Intelligent Control, Beijing Institute of Control Engineering, Beijing 100094, China

Received:2024-06-05 Online:2025-06-25 Published:2025-07-09
Contact: Bin JIANG

摘要/Abstract

摘要：

针对无人艇(unmanned surface vessel, USV)在障碍地图中的避碰路径规划问题, 提出一种基于改进蚁群算法的静态全局路径规划避碰方法, 并面向未知障碍给出一种局部路径重规划方案。运用栅格法对障碍环境进行建模; 通过设计复合启发函数, 提出一种信息素动态给予机制, 引入混沌优化算子, 解决传统蚁群算法易落入局部最优解和收敛性差的问题; 基于鱼群效应提出一种局部路径重规划方案, 解决USV编队在遭遇未知障碍时的路径重规划问题。对由5艘USV组成的分布式编队系统进行仿真实验, 验证了所提方法对编队避碰问题的有效性。

关键词: 无人艇编队, 路径规划, 路径重规划, 改进蚁群算法, 混沌优化

Abstract:

In view of the problem of collision avoidance path planning for unmanned surface vessel (USV) in obstacle maps, a static global path planning collision avoidance method based on improved ant colony algorithm and a local path re-planning scheme for unknown obstacles are proposed. The grid method is used to model the obstacle environment. By designing a composite heuristic function, proposing a dynamic pheromone giving mechanism, and introducing a chaotic optimization operator, the problems of traditional ant colony algorithms being prone to falling into local optima and having poor convergence are solved. Furthermore, based on the fish schooling effect, a local path re-planning scheme is proposed to solve the path re-planning problem of USV formations when encountering unknown obstacles. Simulation experiments on a distributed formation system consisting of five USVs are conducted to verify the effectiveness of the proposed method for collision avoidance in formation.

Key words: unmanned surface vessel (USV) formation, path planning, path re-planning, improved ant colony algorithm, chaos optimization

中图分类号:

TP202.7

刘伊婕, 姜斌, 马亚杰, 李文博, 刘成瑞. 无人艇编队避碰路径规划与重规划[J]. 系统工程与电子技术, 2025, 47(6): 1964-1974.

Yijie LIU, Bin JIANG, Yajie MA, Wenbo LI, Chengrui LIU. Collision avoidance path planning and re-planning for USV formation[J]. Systems Engineering and Electronics, 2025, 47(6): 1964-1974.

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参考文献 31

1	JORGEV A M,GRANADAR,MAIDANAR G,et al.A survey on unmanned surface vehicles for disaster robotics: main challenges and directions[J].Sensors,2019,19(3):702. doi: 10.3390/s19030702
2	SUNH B,SHIJ R,HOUL L,et al.Dynamic event-triggered output feedback fault-tolerant control for dynamic positioning of unmanned surface vehicles with multiple estimators[J].IEEE Trans.on Vehicular Technology,2024,73(3):3218-3229. doi: 10.1109/TVT.2023.3327265
3	LIY M,FENGK L,LIK W.Finite-time fuzzy adaptive dynamic event-triggered formation tracking control for USVs with actuator faults and multiple constraints[J].IEEE Trans.on Industrial Informatics,2024,20(4):5285-5296. doi: 10.1109/TII.2023.3331101
4	FANY S,SUNX J,WANGG F,et al.Collision avoidance controller for unmanned surface vehicle based on improved cuckoo search algorithm[J].Applied Sciences,2021,11(20):9741. doi: 10.3390/app11209741
5	MAOZ H,JIANGB,SHIP.Fault-tolerant control for a class of nonlinear sampled-data systems via a Euler approximate observer[J].Automatica,2010,46(11):1852-1859. doi: 10.1016/j.automatica.2010.06.052
6	MAY J,JIANGB,TAOG,et al.Uncertainty decomposition based fault-tolerant adaptive control of flexible spacecraft[J].IEEE Trans.on Aerospace and Electronic Systems,2015,51(2):1053-1068. doi: 10.1109/TAES.2014.130032
7	SONGR,LIUY C,BUCKNALLR.Smoothed A* algorithm for practical unmanned surface vehicle path planning[J].Applied Ocean Research,2019,83,9-20. doi: 10.1016/j.apor.2018.12.001
8	LIX H,YUS H,GAOX Z,et al.Path planning and obstacle avoidance control of UUV based on an enhanced A* algorithm and MPC in dynamic environment[J].Ocean Engineering,2024,302,117584. doi: 10.1016/j.oceaneng.2024.117584
9	SONGJ,HAOC,SUJ C.Path planning for unmanned surface vehicle based on predictive artificial potential field[J].International Journal of Advanced Robotic Systems,2020,17(2) doi: 10.1177/1729881420918461
10	ZHANGW L,SHANL,CHANGL,et al.SVF-RRT: a stream-based VF-RRT for USVs path planning considering ocean currents[J].IEEE Robotics and Automation Letters,2023,8(4):2413-2420. doi: 10.1109/LRA.2023.3245409
11	XIAG Q,HANZ W,ZHAOB,et al.Global path planning for unmanned surface vehicle based on improved quantum ant colony algorithm[J].Mathematical Problems in Engineering,2019,2019,2902170. doi: 10.1155/2019/2902170
12	CUIY N,RENJ,ZHANGY.Path planning algorithm for un manned surface vehicle based on optimized ant colony algorithm[J].IEEJ Transactions on Electrical and Electronic Engineering,2022,17(7):1027-1037. doi: 10.1002/tee.23592
13	ZHANGJ,DUX,DONGQ C,et al.Distributed collaborative complete coverage path planning based on hybrid strategy[J].Journal of Systems Engineering and Electronics,2024,35(2):463-472. doi: 10.23919/JSEE.2023.000118
14	XINJ F,ZHONGJ B,LIS X,et al.Greedy mechanism based particle swarm optimization for path planning problem of an unmanned surface vehicle[J].Sensors,2019,19(21):4620. doi: 10.3390/s19214620
15	LUOJ,LIANGQ C,LIH.UAV penetration mission path planning based on improved holonic particle swarm optimization[J].Journal of Systems Engineering and Electronics,2023,34(1):197-213. doi: 10.23919/JSEE.2022.000132
16	赵贵祥,周健,李云淼,等.改进双向快速搜索随机树的无人艇路径规划[J].系统工程与电子技术,2024,46(4):1364-1371.
	ZHAOG X,ZHOUJ,LIY M,et al.Improved bi-directional rapidly-exploring random tree path planning for USV[J].Systems Engineering and Electronics,2024,46(4):1364-1371.
17	LINC J,WANGH J,YUANJ Y,et al.An improved recurrent neural network for unmanned underwater vehicle online obstacle avoidance[J].Ocean Engineering,2019,189,106327. doi: 10.1016/j.oceaneng.2019.106327
18	GUOS Y,ZHANGX G,ZHENGY S,et al.An autonomous path planning model for unmanned ships based on deep reinforcement learning[J].Sensors,2020,20(2):426. doi: 10.3390/s20020426
19	陈岱岱,李玩幽.带拖线阵的水面无人艇局部路径规划算法[J].系统工程与电子技术,2020,42(9):1988-1994. doi: 10.3969/j.issn.1001-506X.2020.09.14
	CHEND D,LIW Y.Local path planning algorithm for USV with towed cable[J].Systems Engineering and Electronics,2020,42(9):1988-1994. doi: 10.3969/j.issn.1001-506X.2020.09.14
20	ZHUANG Y F, DONG H R, HUANG H B, et al. Dynamic path planning of USV based on improved artificial potential field method in harsh environment[C]//Proc. of the China Automation Congress, 2022: 5391-5396.
21	赵贵祥,王晨旭,王贺平,等.改进速度障碍法的无人艇局部路径规划[J].系统工程与电子技术,2023,45(12):3975-3983. doi: 10.12305/j.issn.1001-506X.2023.12.28
	ZHAOG X,WANGC X,WANGH P,et al.Local path planning for unmanned surface vehicle using improved velocity obstacle method[J].Systems Engineering and Electronics,2023,45(12):3975-3983. doi: 10.12305/j.issn.1001-506X.2023.12.28
22	李文刚,汪流江,方德翔,等.联合A与动态窗口法的路径规划算法[J].系统工程与电子技术,2021,43(12):3694-3702. doi: 10.12305/j.issn.1001-506X.2021.12.33
	LIW G,WANGL J,FANGD X,et al.Path planning algorithm combining A with DWA[J].Systems Engineering and Electronics,2021,43(12):3694-3702. doi: 10.12305/j.issn.1001-506X.2021.12.33
23	YANX,JIANGD P,MIAOR L,et al.Formation control and obstacle avoidance algorithm of a multi-USV system based on virtual structure and artificial potential field[J].Journal of Marine Science and Engineering,2021,9(2):161. doi: 10.3390/jmse9020161
24	WEIX W,WANGH,TANGY X.Deep hierarchical reinforcement learning based formation planning for multiple unmanned surface vehicles with experimental results[J].Ocean Engineering,2023,286(2):115577.
25	ZHANGJ,CUIY,FANX Z,et al.Asynchronous multi-threading reinforcement control decision method for unmanned surface vessel[J].IEEE Internet of Things Journal,2023,10(24):22806-22822. doi: 10.1109/JIOT.2023.3305387
26	WANGD,CHENH M,LAOS H,et al.Efficient path planning and dynamic obstacle avoidance in edge for safe navigation of USV[J].IEEE Internet of Things Journal,2024,11(6):10084-10094. doi: 10.1109/JIOT.2023.3325234
27	HES D,WANGM,DAIS L,et al.Leader-follower formation control of USVs with prescribed performance and collision avoidance[J].IEEE Trans.on Industrial Informatics,2019,15(1):572-581. doi: 10.1109/TII.2018.2839739
28	HAND D,MINL Q,ZHANGH Y,et al.Robust chaos of cubic polynomial discrete maps with application to pseudorandom number generators[J].Mathematical Problems in Engineering,2019,2019,8250903. doi: 10.1155/2019/8250903
29	RAHMANM S.Basic graph theory[M].Berlin:Springer,2017:11-12.
30	REN W. Consensus based formation control strategies for multi-vehicle systems[C]//Proc. of the American Control Conference, 2006: 4237-4242.
31	王常虹,刘博,李清华.集群多机器人系统建模研究的发展与展望[J].导航定位与授时,2021,8(1):1-13.
	WANGC H,LIUB,LIQ H.Development and prospect of research on modeling of swarm multi-robot system[J].Navigation Positioning and Timing,2021,8(1):1-13.

参数	地图维数
参数	20	40	60
迭代次数	100	300	500
蚂蚁数量/只	10	30	50
栅格长度/m	1 000	1 000	1 000

参数	无人艇编号/位置	数值
环境尺寸/m	—	(20 000, 20 000)
初始位置/m	虚拟领航艇	(500, 19 500)
	1号无人艇	(450, 19 530)
	2号无人艇	(400, 19 550)
	3号无人艇	(400, 19 450)
	4号无人艇	(400, 19 550)
	5号无人艇	(350, 19 450)
初始速度/kn	虚拟领航艇	(0, 1×463/900)
初始速度/kn	试验无人艇	(0, 0)
最大速度/kn	虚拟领航艇	12×463/900
最大速度/kn	试验无人艇	15×463/900
编队构型/m	(x₁₀, y₁₀)	(0, 0)
	(x₂₀, y₂₀)	(-50, 50)
	(x₃₀, y₃₀)	(-50, -50)
	(x₄₀, y₄₀)	(-100, 50)
	(x₅₀, y₅₀)	(-100, -50)
最大加速度/(m/s²)	—	0.5
γ	—	1

参数	数值
位置/m	(3 000, 17 000)
障碍物半径/m	150
安全距离R_s/m	20

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无人艇编队避碰路径规划与重规划

Collision avoidance path planning and re-planning for USV formation

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